Technical Reference🔗
The PlanktoScope is a modular, open-source platform for high-throughput quantitative imaging of plankton samples. Its small size, ease of use, and low cost make it suitable for a variety of applications, including the monitoring of laboratory cultures or natural micro-plankton communities. It can be controlled from any WiFi-enabled device and can be easily reconfigured to meet the changing needs of the user.
Key Features🔗
Here are some key features of the PlanktoScope:
- Low cost: The PlanktoScope is designed to be affordable, with parts costing under $1000.
- Modular: The PlanktoScope is modular, meaning it can be easily reconfigured to meet the changing needs of users.
- Open-source: The PlanktoScope is based on open-source hardware and software, making it accessible to a wide community of engineers, researchers, and citizens.
- Versatility: The PlanktoScope is versatile, and can be used to study a variety of plankton types, including laboratory cultures and natural micro-plankton communities.
- High-throughput: The PlanktoScope is capable of high-throughput quantitative imaging, allowing users to analyze large numbers of samples quickly and efficiently.
- WiFi-enabled: The PlanktoScope can be controlled from any WiFi-enabled device, making it easy to use and deploy in a variety of settings.
- Portable: The PlanktoScope is small and portable, making it easy to transport and use in the field.
- Ease of use: The PlanktoScope is designed to be easy to use, with instructions for assembly and use available on the PlanktoScope website.
Device specification🔗
Size🔗
- height: 105 mm
- wide: 275 mm
- depth: 125 mm
Hardware🔗
- 4 Core ARM-Cortex-A72 Processor with 1,50 GHz
- 4 GB Arbeitsspeicher (depending on the purchased version)
- 64 GB Flash memory (depending on the purchased version)
- Sony IMX477R Image sensor with 12.3MP
- M12 mount optics with 16 and 25 mm lenses
- Automatic focus via linear guide
- automatic sampling via peristaltic pump
- the case is made of wood fiberboard
Software🔗
- Debian based Embedded Linux operating
- Node-Red based user interface
- Python Image processing service and cloud connection
Characteristic🔗
- Focus stage control
- Pump control
- Automatic image capture
- Automatic segmentation, optimization and object detection
- Control via smartphone or tablet
Areas of Application🔗
- Plankton analysis of small animals and algae living in water
- Mobile use via external power supply
System Requirements🔗
- a Web-Browser to control the device (like a Notebook, Smartphone or Tablet)